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1 MUCOSAL IMMUNITY AND TYPE 1 DIABETES By MICHAEL RYAN NELSON A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSIT Y OF FLORIDA 2013
2 2013 Michael Ryan Nelson
3 To my Mom and Dad who have always been there
4 ACKNOWLEDGMENTS I would like to thank my parents, family and friends who have supported me in all of my endeavor s. I would like to thank Dr. Shannon Wallet who has always believed in me and supported me in all my decisions. I would like to thank Dr. Marguerite Hatch for mentoring me throughout this project.
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................. 4 L IST OF TABLES ............................................................................................................ 7 LIST OF FIGURES .......................................................................................................... 8 LIST OF ABBREVIATIONS ............................................................................................. 9 ABSTRA CT ................................................................................................................... 12 CHAPTER 1 INTRODUCTION ........................................................................................................ 14 Diabetes Mellitus .................................................................................................... 14 Type 1 Diabetes ...................................................................................................... 14 Epidemiology of T1D ............................................................................................... 15 NOD Mouse Model ................................................................................................. 18 NOD Mouse Dise ase Progression .......................................................................... 19 T1D Pathology ........................................................................................................ 20 Antigen Presenting Cells .................................................................................. 20 Macrophages .................................................................................................... 21 Dendritic Cells .................................................................................................. 21 B Cells .............................................................................................................. 22 Autoantibodies .................................................................................................. 23 T cells ............................................................................................................... 23 Immune Regulation .......................................................................................... 24 Thymic Selection .............................................................................................. 24 Peripheral Regulation ....................................................................................... 25 Environmental Contributions ................................................................................... 26 Mucosal Immunity ................................................................................................... 27 Intestinal Epithelial Cells ................................................................................... 28 Intestinal Macrophages .................................................................................... 29 Intestin al Dendritic Cells ................................................................................... 29 Regulatory T cells and Mucosal Tolerance ....................................................... 31 Th17 Cells ........................................................................................................ 32 Mucosal Immunity and T1D .................................................................................... 35 Diet and T1D .................................................................................................... 35 Evidence of Mucosal Inflammation in T1D ....................................................... 35 Gastrointestinal Alterations in T1D ................................................................... 36 Hypothesis and Summary ................................................................................ 38 2 MATERIALS AND METHODS ................................................................................... 39
6 Murine Models ........................................................................................................ 39 Gastrointestinal Permeability .................................................................................. 39 Flow Cytome try ....................................................................................................... 40 ELISA ...................................................................................................................... 41 Statistics ................................................................................................................. 42 3 RESULTS ................................................................................................................... 43 Intestinal Permeability ............................................................................................. 44 Movement of Charged Ion Differs between NOD and B6 Mice ............................... 45 Preliminary Flux Trials ............................................................................................ 45 70kDa Dextran as a Paracellular Permeability Marker ............................................ 46 when Compared to B6 ............ 47 T cell Population Differences between NOD and B6 Mice ...................................... 48 Th17 and Th1 Differences between NOD and B6 Mic e .......................................... 49 NOD MLN and PLN T cell Populations over the Course of the Disease ................. 50 Decreased Treg Frequency in the MLN and PLN of NOD Mic e .............................. 51 4 DISCUSSION ............................................................................................................. 63 LIST OF REFERRENCES ............................................................................................. 68 BIOGRAPHICAL SKETCH ............................................................................................ 90
7 LIST OF TABLES Table page 3 1 Gastrointestinal Barrier Function Analysis. ......................................................... 52
8 LIST OF FIGURES Figure page 3 1 Temporal Evaluation of Intestinal Barrier Function and Inflammation ................. 53 3 2 Decreased Gastrointestinal Movement of Charged Ions in NOD mice. .............. 54 3 3 Optimization of Gastrointestinal Permeability Assays. ........................................ 55 3 4 Evaluation of 70kDa Dextran as a Paracellular Permeability Marker. ................ 56 3 5 NOD mice exhibit Elevated Duodenal TNF Levels.. ......................................... 57 3 6 Gating schemes for Flow Cytometric Analysis.. .................................................. 58 3 7 Frequencies of Polarized T cells in the MLN and PLN.. ..................................... 59 3 8 Frequencies of IL17 expressing T cell populations. ............................................ 60 3 9 Distribution of T cell populations within the MLN and PLN of NOD mice over the course of disease.. ....................................................................................... 61 3 10 Decreased Frequencies of Tregs in the MLN and PLN of NOD mice.. ............... 62
9 LIST OF ABBREVIATIONS APC Antigen Presenting Cells B6 C57Bl/6 mice BBDP Bio Breeding Diabetes Prone Rats CIA Collageninduced Arthritis CTE Cortical Thymic Epithelia l Cells CTLA 4 Cytotoxic T Lymphocyte Antigen 4 DC Dendritic Cells DC Distal Colon DI Distal Ileum DP Double Positive Thymocytes EAE Experimental Autoimmune Encephalomyelitis EGFR Epidermal Growth Factor Receptor FoxP3 Forkhead Box P3 Treg transcription factor GAD65 Glutamate Decarboxylase 65 GDM Gestational Diabetes Mellitus GI Gastrointestinal GT Tissue Conductance HLA Human Leukocyte Antigen IA 2 Insulinoma antigen 2 IAA Insulin Autoantibody IBD Inflammatory Bowel Disease ICA Islet Cell Antibodies IDO Indoleamine 2,3dioxygenase IEC Intestinal Epithelial Cells
10 IEL Intraepithelial Lymphocytes Interferon Gamma IGF 1 Insulin like growth factor 1 IGRP islet specific glucose 6 phosphatase catalytic subunit related protein IL2 Interleukin2 IL17 Interleukin17 Isc Short Circuit Current Jdex Dextran Flux Jman Mannitol Flux LP Lamina Propria LYP Lymphoid Tyrosine Phosphatase MAdCAM 1 Mucosal Addressin Cell Adhesion Molecule 1 MHC Major Histocompatibility Complex MLN Mesenteric Lymph Node NOD Non Obese Diabetic Mice PAMP Pathogen Associated Molecular Patterns PAR2 Proteinaseactivated Receptor 2 PL N Pancreatic Lymph Node PP Peyers Patches PJ Proximal Jejunum RA Retinoic Acid RARrelated Orphan Receptor Gamma Th17 transcription factor T1D Type 1 Diabetes TCR T Cell Receptor TGF Transforming Growth Factor
11 TJ Tight Junctions TLR Toll Like Receptors Tumor Necrosis Factor Alpha TREG Regulatory T cells VNTR Variable Number of Tandem Repeats
12 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science MUCOSAL IMMUNITY AND TYPE 1 DIABETES By Michael R yan Nelson August 2013 Chair: Shannon Wallet Major: Medical Sciences The initiating events that lead to autoimmunity which results in the destruction of cells in type 1 diabetes (T1D) have yet to be defined. Increasing evidence suggests an involvement of the mucosal immune system in the pathogenesis of T1D. A leaky gut preceding the onset of T1D has been observed in both humans and in rodent models. Additionally, diseasecausing T cells have been found in the draining lymph nodes of the gastrointestinal tract in rodent models. Together, this suggest s that a breakdown of barrier function and inflammation in the gastrointestinal tract may contribute to the induction of autoimmunity. Thus we hypothesized that a breakdown in intestinal barrier function results in an inflammatory environment that promotes nontolerizing conditions. It was determined that in a murine model of T1D, the nonobese diabetic ( NOD ) mice decreased transcellular ion movement but no differences in paracellular movement were exhibited. NOD mice also exhibited elevated levels of duodenal Th1, conventional Th17, and pathogenic Th17 CD4 T cells compared to B6 mice along with decreased frequencies of regulatory T cells. Most importantly, these populations changed over the course of the disease within NOD mice in a trend supporting intestinal inflammation
13 early in disease leading to pancreatic inflammation later in disease. In summary work presented here has added to the evidence that aberrant gastrointestinal barrier function and inflammation contributes to T1D pathogenesis.
14 CHAPTER 1 INTRODUCTION Diabetes Mellitus Diabetes mellitus is a metabolic disease characterized by chronic hyperglycemia due to defects in insulin secretion, insulin action, or both. There are multiple classifications of diabetes mellitus including: type 1 diabetes, type 2 diabetes, and gestational diabetes. Type 1 diabetes (T1D) is a form of diabetes characterized by loss cells, which are the insulin producing cells, and results in hyperglycemia1. Type 2 diabetes (T2D) is the most common form of diabetes and is characterized by disorders in insulin action. T2D patients exhibit insulin resistance rather than insulin defi ciency1. Gestational diabetes mellitus (GDM) is a form of diabetes that occurs during onset of pregnancy characterized by hyperglycemia2, 3. T ype 1 Diabetes Type (T1D) is a chronic inflammatory disease characterized by hyperglycemia due to loss of the insulin producing pancr cells within the islets of Langerhans. T1D is classified into primarily two forms: type 1A or 1B. Type 1B occurs due to cells without presentation of autoimmune antibodies or evidence of autoimmunity 4. The more common form of T1D is type 1A which is characterized by autoimmun cells 5. Both forms of T1D result in insulin deficiency and hyperglycemia which can cause complications such as retinopathy, diabetic nephropathy, peripheral neuropathy, and cardiovascular disease (reviewed in 6). Well controlled glycemic levels can reduce these disease associated complications (reviewed in 6). The focus here will be on type 1A autoimmune diabetes
15 and the role of the mucosal immune system in development and progression of this disease. Epidemiology of T1D T1D is the major type of diabetes effecting youth causing 85% of all diabetes cases in individuals less than 20 years old worldwide 79. I ncidence of T1D peaks at 1014 years of age, starts to decline after puberty and stabilizes during young adulthood 1013. The DIAMOND project initiated by the World Health Organization (WHO) demonstrated that worldwide distribution of T1D varies greatly 14. The lowest incidence rate was reported for populations in China and South America (<1/100,000 per year) while the highest incidence rate was reported for populations in Sardinia, Finland, Sweden, Norway, Portugal, UK, Canada, and New Zealand (>20/100,000) 14. The difference in incidence was suggested to be due to differences in genetic admixture or a result of environmental and/or behavioral differences 15. For instance, effects of birth season on incidence were observed in the SEARCH study. The ratio of observed to expected incidence in births during the w inter months (November February) was low while the same ratio was higher in summer months (April July). T his seasonal pattern was observed in northern locations such as Colorado, Washington, and Ohio, but not southern locations such as South Carolina, Southern California, or Hawaii 16. It has been hypothesized that these variations in incidence are due to seasonal variations in the maternal vitamin D levels due to geographical location 15. These epidemiological observations suggest that along with genetic susceptibility there are environmental factors which contribute to the development of the disease that can vary w orldwide
16 T1D Inheritance T1D is a complex multifactorial disease where genetic factors contribute to susceptibility 5. The highest risk factor for T1D is having an identical (monozygotic) twin with the disease. Interestingly, the concordance rate among monozygotic twins was r eported around 30% when looking at a single time point, suggesting that there are other nongenetic factors contributing to disease 1719. It has now come to l ight after following twins who were initially discordant for diabetes that by 60 years of age the cumulative incidence rate is 65%, which still suggests a role for nongenetic factors in contributing to rates of onset of clinical disease20. Studies evaluating the relationships between genetic relatedness within families, between siblings as well as offspring, suggest that T1D development is due to multiple genes combining in an additive fashion to confer risk 21. The strongest genetic risk is linked to the human leukocyte antigen (HLA) region encoding HLA DR and HLA DQ molecules22. Specifically t he haplotypes DQA1*0501DQB1*0201 (DR3) and DQA1*0301DQB1*0302 (DR4) are associated with the genetic risk. The presence of both these haplotypes is found in ~40% of T1D patients 22. On the other hand, the haplotype HLA DQA1*0102DQB1*0602 confers protection 23. In a mouse model for T1D the nonobese diabetic mouse (NOD), susceptibility is also conferred by a major histocompatability complex (MHC) class II molecule I A, termed H 2g7 5, 24. Her e both the beta chain of MHC II I A and the HLA DQ exhibit the same nonaspartic acid substitution at position 57 25, 26. The nonaspartic acid substitution significantly alters the binding partners able to be presented by the MHC molecule 27.
17 In addition to t he HLA region, 40 additional loci have been described as contributing to disease susceptibility 28. Many of the genes associated with these loci have not yet been identified. Some of the few nonMHC genes that have been defined include a singlenucleotide polymorphism in the lymphoid tyrosine phosphatase (LYP) encoded by the PTPN2 gene, allelic variations in cytotoxic T lymphocyte antigen 4 (CTLA 4), a polymorphic region variable number of tandem repeats (VNTR) located immediately 5' the insulin gene as well as variations in the IL2 and IL2Rra gene region26 36. LYP plays a role in T cell receptor (TCR) signaling and a singlenucelotide polymorphism has been associated with autoimmune diseases, including T1D 29. This singlenucleotide polymorphism in LYP was shown to cause a gain of function resulting in more mobilization and IL2 gene transactivation 30. Thus, the polymorphism causes a more active phosphatase which can suppress TCR signaling more efficiently than normal LYP. CTLA 4 plays a role in maintaining regulatory T cell ( Treg) function as well as downregulating effector T cell responses 31, 32. In humans, T1D is associated with a Ctla 4 variant that results in decreased expression of the soluble form of CLTA 4 31. In NOD mice, T1D is associated with low levels of a splice variant of Ctla 4 that lacks the domain which binds with the costimulatory markers, CD80/86 32, 33. The VNTR element of the insulin gene promoter has been shown in humans to result in decreased thymic expression of the insulin gene 34, 35. This VNTR allele is not present in NOD mice, but studies in the NOD demonstrate that alterations in thymic
18 insulin expression contribute to disease 36, 37. In rodents there are tw o different insulin genes, ins1 and ins2 which are located on two different chromosomes. The ins2 gene is thought to be preferentially expressed over ins1 in the thymus 38. By selectively decreasing expression of ins2 in the thymus it has been shown that ins2 deficient NOD mice exhibit earlier onset of disease compared to wildtype NOD mice 36, 37. In humans hypomorphic polymorphisms of IL2 and IL2ra are linked to autoimmune susceptibility 3942. In NOD mice, lower levels of IL 2 are associated with disease progression whereby treatment with IL 2 can inhibit the onset of clinical diabetes 43, 44. In addition, a loss of one copy of the IL2 allele can accelerate onset of T1D 41. Though these susceptibility loci are not completely conserved between humans and mice, the similarities between them make the NOD mouse a good model for understanding development of the disease. NOD Mouse Model I n human T1D, there is an asym ptomatic preclinical phase where an autoimmune process is initiated, but t he autoimmune process leading to destruction of the pancreatic cells is difficult to study due to t he inaccessibility of the pancreas Thus, i n order to decipher t he initiating and progressive autoimmune events leading to the destruction of cells animal models that develop spontaneous autoimmune disease resulting in cells, have been utilized. The NOD mouse strain was developed through inbreeding of the ICR (Swiss) mice in Japan 45. Dr. S Makino at the Shionogi Research Laboratories in Aburahi, Japan was developing a strain by selecting for dominant cataract with microphthalmia 4547. After six generations (F6) a subset of mice began exhibiting high fasting glucose levels and was thus inbred selecting for this trait. At the same time, progeny that
19 exhibited normal fasting glucose levels were inbred as a euglycemic control strain. Interestingly, the first mouse to spontaneously develop hyperglycemia and exhibit insulitis actually came from the strain being in bred as the euglycemic control. This female mouse was the founder of the NOD strain 4547. NOD Mouse Disease Progression The majority of what we know regarding local cellular events that contribute to autoimmune destruction of islets within the pancreas has been learned from the NOD mouse. T he progression of cell autoimmun ity in the NOD mouse is broken down into well defined checkpoints 48. The first checkpoint occurs around 3 weeks of age and is characterized by infiltration of the islets by immune cells 4851. Invading immune cells consist of both innate and adaptive immune cells where the majority are CD4 + and CD8 + T cells, B cells, dendritic cells (DC), NK cells, and macrophages 46, 47. During this first checkpoint infiltration continues until about 1012 cells remain intact and mice remain euglycemic even in cases with severe insulitis 48. The second c heckpoint is characterized by a switch in the pathogenic potential of the cell destruction occurs resulting in eventual development of hyperglycemia known as overt diabetes 48. Both CD4+ and CD8+ T cells can directly mediate islet cell destruction, though some studies suggest that a CD8 + response occurs early in disease resulting in islet death and priming of the CD4 + res ponse 52. Despite understanding the two checkpoints of NOD disease progression, the initiation of the autoimmune process and the switch in pathogenic potential bet ween Checkpoint 1 and 2 are still not understood. Some insight into this pathogenic switch has been gained by using BDC2.5 mice, cell antigens. In this mouse
20 model, the mice exhibit insulitis yet only 1020% of the BDC2.5 mice develop overt diabetes 53. This may be due to the presence of a high number of Tregs contributing to cell death, suggesting a role for peripheral tolerance regulating movement from Checkpoint 1 to 2 54. While the NOD model shares many similarities with human disease and many of the discoveries involving pathogenesis have come to light using the NOD model 55, translating therapeutic approaches from NOD mice to humans has been difficult. These difficulties are most likely due to the fact that there are some differences in the etiology of disease between NOD and humans. For example there are differences i n target antigens, the composition of inflammatory infiltrates, as well as an increased expression of MHC class I in humans 56. Despite these differences, NOD m ice still prove to be a good model for describing the role of the adaptive immune response in the pathology of the disease as well as identifying therapeutic targets. T1D Pathology T hough diabetogenic T cells (CD4+ and CD8+ T cells) are key players in the cells in T1D for both humans and NOD mice, there are many other cell types of both the innate and adaptive immune system that are involved with development and progression of disease. Antigen Presenting Cells Antigen presenting cells (APC ), including macrophages, dendritic cells (DCs), and B cells, play an important role in bridging the gap between innate and adaptive immunity. APC induce T cell responses by TCR activation, through recognition of peptides presented on MHC molecules, and co stimulatory signals 57. In the absence of co stimulatory signals T cells become anergic and/or undergo apoptosis 58. Because
21 APC are able to prime and activate T cells as well as regulate T cell responses, they play a critical role in development of autoimmunity 59, 60. Macrophages Macrophages can be detected in the islets of NOD mice early in disease. Their depletion can prevent t he development of disease 61. In vivo and in vitro studies have cell death through production of 62, 63. Interestingly, macrophages in NOD mice are less efficient at engulfing apoptotic cells, which results in accumulation of dying cells or debris that promote inflammatory responses 64. Some have suggested that these products released by dying cells are the initiators of disease development 65. Dendritic Cells While DCs are integral in T cell activation, they are also critical in peripheral tolerance because they can also induce T cell deletion, T cell anergy, and expansion of Tregs, all of which are critical for the prevention of autoimmunity including T1D 57. Evidence for a role for DC in peripheral tolerance is highlighted in studies where DC depletion results in autoimmune disease 66. In the NOD mouse DC take up islet self cell death, process, and present these antigens to islet specific T cells located within the pancreatic lymph nodes (PLNs) 67. Here DC from NOD mice have an increased ability to activate T cells through higher expression of IL12 as well as higher expression of costimulatory molecules compared to C57Bl/6 mice 68, 69. In addition there is an increas ed frequency of type 1 IFN producing DC in the pancreatic lymph node during T1D initiation, which could contribute to autoimmune T cell activation 70. These studies suggest that in T1D there is an enhance ability of DC to activate T cells.
22 On the other hand, the tolerogenic potential of DC in T1D is diminished. For instance, indoleamine 2,3dioxygenase (IDO) expression by DC in young NOD mice is decreased 71. IDO expression by DC controls effector T cell expansion by catabolism of tryptophan, which is necessary for T cell proliferation and expansion. Thus less IDO production allows for increased T cell survival 72. Indeed, over expression of IDO in NOD can extend islet graft survival 73. Other studies have investigated FMS l ike tyrosine kinase (Flt3) ligand, which promotes tolerogenic DC that enhance Treg frequency in the PLN 74, 75. Interestingly, early administration of Flt3ligand in the NOD is protective, while late stage administration actually expands DC populations exacerbating T1D development 76. These data suggest that tolerance may only be able to be achieved at early stages of the disease. B Cells B cells serve not only as APCs but also as a source for autoantibodies. Autoantibodies have not been shown to have a direct effector function in the destruction of cells 77, 78. In fact, a study using B cells that cannot secrete antibodies demonstrated that B cells play an antibody independent role in the development of disease 79. On the other hand, B cell deficiency achieved through gene targeting or through antibody mediated depletion prevents development of the disease in NOD mice 80. Similar effects are seen in humans, wher cell function in newly diagnosed patients 81. Though they do not present antigens as efficiently as DC, it has been s uggested that the antigen specific B cells are acting as APC 82. B cells actually i nternalize antigen 10,000fold more efficiently than nonspecific cells 83, 84. In
23 this way, B cells c an internalize a much greater range of peptides from the protein or proteins associated with it and diversify the CD4+ T cell response 85. Autoantibodies D etect ion of autoantibodies is considered a predictor of T1D where the presence of autoantibodies at younger ages and at higher ti t ters correlates to disease development 78, 8688. Islet cell antibodies (ICA) were first observed in the islets of human pancreatic tissue samples 89. Since then, studies have determined the targets of these autoantibodies to be insulin (insulin autoantibody, IAA), glutamic acid decarboxylase 65 (GAD65), and insulinomaassociated protein 2 (IA 2) [reviewed in 90] NOD mice also exhibit autoantibodies towards insulin 77, but only low levels of autoantibodies against GAD65 and IA 2 91. Though autoantibodies are considered a risk factor, they are not consider ed to be a factor contributing to islet destruction cell specific autoantibodies can be detected in first degree relatives though they may not progress to overt disease 90. Similarly, in NOD mice, autoantibody transfer from new onset donors cannot transfer disease 82. T cells Both CD4+ and CD8+ T cells are key players cells. This is highlighted by the fact that adoptive transfer of purified populations of CD4+ or CD8+ T cells from NOD donors as well as T cells clones generated from infiltrated islets cause disease 92 96. cells expressing MHC I through perforin/granzyme secretion 97. CD4+ T cells that recognize MHC II presented peptides such as dendritic cells and macrophages 97.
24 A cell antigens within peripheral blood can be found in both NOD mice and humans with T1D Here CD4+ and CD8+ T cells recognizing GAD65 and insulin have been identified 90. Unlike in humans, NOD mice also have CD8+ T cells that recognize IGRP which comprises about 40% of the CD8+ T cells in the islets of NOD mice 98, 99. Other autoreactive T cell identified include those that recognize heat shock protein 60 98, 100102. Immune Regulation Ineffective central and peripheral immune regulation contributes to the development of T1D. In NOD mice, there are several studies suggesting ineffective thymic selection and peripheral regulation. Thymic Selection In the thymus, T cells undergo positive selection where double positive (DP), C D4+ CD8+, cells interact with cortical thymic epithelial cells (CTE) that express MHC I and MHC II. T cells that have TCR that can recognize MHC I or MHC II receive signals to survive, while T cells with TCR that cannot recognize peptideMHC complexes die 103, 104 This is known as positive selection and is a key step in the induction of natural CD4+CD25+ regulatory cells 103, 104. Following positive selection T cells undergo negative selection where T cel ls that strongly recognize self antigen undergo apoptosis 104. It has been proposed that the I Ag7 MHC class II in NOD mice and the diabetogenic HLA DR and DQ alleles in humans contribute to inefficient negative selection, thereby allowing more autoreactive T cells to make escape into the periphery105. IAg7 has been shown to poorly bind self peptides which doesnt allow for a strong interaction with DP cells necessary for negative selection106, 107. In addition, in
25 NOD mice, it has been shown that the CTE are inefficient at inducing CD4+CD25+ Tregs 108. Together these data demonstrate alterations in central immune regulation in T1D. Peripheral Regulation In addition to ineffective thymic selection, there are deficits in peripheral tolerance, which is primarily mediated by Tregs, in T1D. The major function of Tregs is to suppress activation and proliferation of T lymphocytes 109 in order to eliminate excessive activation which could lead to prolonged host damage or autoimmune diseases. Tregs are typically characterized by expression of CD25+ the chain of the high affinity IL2 receptor 110, and the transcription factor forkhead box P3 (FoxP3) 111. Tregs have different mechanisms of suppression through direct interaction with effector T cells or through interactions with APC. Tregs are able to suppress T cell responses through the inhibitory effects of IL10 and TGFcell immunosuppression 112, while soluble IL10 induces inhibition of signaling through the costimul atory molecule CD28 113. Importantly Tregs are able to inhibit the induction of IL2 mRNA in effector T cells; an important proliferative signal for T cells 114116. Tregs can also mediate cytolysis of effector T cells. In humans, activated Tregs express granzyme A and thus can kill CD4+ and CD8+ T cells in a perforindependent, Fas FasL independent manner 117, 118. In mice, activation of Tregs results in upregulation of granzyme B whereby granzymeB d eficient Tregs had reduced suppressive activity 119. A number of studies have shown that Tregs downregulate expression of costimulatory molecules on both human and mouse DC 120, 121. Interactions of CTLA 4, located on the Tregs, with CD80 and CD86, located on the A PC 122, prevents increased
26 expression of CD80 and CD86 effectively limiting their abilities to stimulate naive T cells through CD28 123. In addition, CTLA 4 on Tregs interacting with CD80 and CD86 on APC has also been shown to upregulate expression of IDO, which can inhibit T cell proliferation 124. The importance of Tregs has been demonstrated using depletion of regulatory T cells or DEREG mice which leads to severe autoimmune disease and death upon Treg depletion. DER EG mice express a diphtheria toxin (DT) receptor enhanced green fluorescent protein fusion protein under the control of the foxp3gene locus and deplet ion of Tregs can be achieved upon injection of diphtheria toxin 125. Specific to T1D, as mentioned previously, BDC2.5 mice exhibit insulitis yet only 1020% of the BDC2.5 mice develop diabetes, most likely due to regulation by Tregs 53, 54. In humans, mutations in forkhead box p3 ( FOXP3 ), a Treg transcription factor, have been observed in several autoimmune diseases i ncluding T1D126. Together these models suggest that Tregs play an integral role in the loss of peripheral tolerance, the cell destruction, and eventual development of clinical disease. Environmental Contributions The incidence rate of T1D has been increasing over the past century faster than can be accounted for by genetics, suggesting that there are nongenetic factors contributing to initiation and or progression of disease 127. There are a number of observations suggesting an environmental contribution. 1) A low concordance rate and differing rates of onset of T1D between monozygotic twins (65% when followed out to age 60) 1719 128 and 2) difference s in incidence between the transmigratory population and their homeland counterparts despite genetic similarity 12, 129, 130. For instance, one study demonstrated an increase in the incidence of T1D within Asian families who
27 moved to the UK. The study was conducted over 12 years evaluating subjects aged 016 years within the resident area. They found that the incidence in the Asian children started to approach the incidence rate found within the UK rather than that of their genetic counter parts 130, 131. Some environmental fact ors implicated in the development of the disease include: dietary factors ( such as cereal proteins, cow milk proteins, and vitamin D ) 132, enteroviruses 133, or changes in gut microbiota 134. Additionally, some have suggested t he hygiene hypothesis where exposure to infections early in life helps to train the immune system and thus individuals who are not exposed develop autoimmunity 135. E vidence supporting the hygiene hypothesis is that NOD mice develop diabetes only in a specific pathogen free environment, while housing them in a dirty environment dramatically decreases incidence 92, 136, 137. Each of these environmental factors would closely interact with and effect the mucosal immune system. Thus, many researchers have started to investigate the role of the mucosal immune system in T1D. Mucosal Immunity T he intestinal mucosal system covers a very large surface area (~300 m2 in humans) which is exposed to the external environment. Thus, the mucosal immune system faces the unique challenge of combating pathogens, while still maintaining homeostasis in the presence of bacteria and luminal content. In addition to being the first line of defense for the mucosal immune system, c ommensal bacteria are necessary for dev elopment and maturation of the lymphoid tissues within the mucosal immune system 138143. Specifically, the commensal microbiota can provide protection by competition with pathogenic organisms as well as help develop host natural immunity and tolerance 138143. After the protection granted from the microbiota, the next line of
28 defense involves the intestinal epithelial cells that provide a barrier from the ext ernal environment. Intestinal Epithelial Cells The I ntestinal epithelial cell (IEC) not only absorb nutrients from food, but also functions as a barrier to the external luminal content and as acts an innate immune cell 144, 145 The IEC function to uptake nutrients from the luminal content via two pathways: transcellular and paracellular permeability 146. Transcellular permeability occurs through specific pumps, channels, and transporters 146. Paracellular permeability occurs around or between cells and is regulated by tight junctions (TJ) 146148. Expression of different TJ molecules allows for selective restrictiveness of the molecules allowed to pass 146148. The functions of tight junctions are twofold. First, TJ can function to restrict paracellular permeability and second, TJ allow IEC to form a barrier. TJ are the most apical complexes on IEC responsible for sealing off access from the lumen. Tight junctions are comprised of transmembrane proteins that interact extracellularly with adjacent cells and intracellularly with adaptor proteins that interact with the cytoskeleton 149152. IEC form a single layer which is covered by both mucus and anti microbial products produced by specialized cell types within the gastrointestinal track Specifically, g oblet cells secrete mucus which acts as a protective covering limiting movement within the gastrointestinal track and access to IEC. Paneth cells secrete anti microbial peptides, such as defensins, while IEC secrete the anti microbial peptides, defensins 153, 154. The IEC are constantly being replenished, where damaged, infected, or apoptotic IEC move to the tip of villi to be sloughed off and new IEC arise in the crypt and migrate
29 upwards 153, 154. Interspersed within the IEC are intraepithelial lymphocytes (IEL) that maintain normal homeo stasis. Importantly, while IEL s can regulate IEC, IECs also influence IEL T cell development 155157. Intestinal Macrophages Typically cells within the mucosal immune system regulate homeostasis, but if bacteria do invade the epithelium and the underlying lamina propria (LP) there are various immune mechanisms to prevent systemic infection. For instance, LP residing intestinal macrophages interact closely with the epithelium and quickly take up and eliminate bacteria through the produc tion of antibacterial peptides and reactive oxygen species 158, 159. Although these intestinal macrophages are able to efficiently clear bacteria, they do not elicit a strong proinflammatory immune response 160, 161. Activation of toll like receptors (TLR), receptors that recognize pathogen associated molecular patterns (PAMPs), on intestinal macrophages instead induce production of growth factors such as insulinlike growth factor 1 (IGF1), which induce proliferation of the epithelium in order to repair breaks in the barrier 162, 163. In addition t o regulating epithelial cell homeostasis, intestinal macrophages have been implicated in generation of FoxP3+ regulatory T cells (Tregs) through expression of IL10 164. Thus, if a breakdown in barrier integrity occurs and there is in an aberrantly inflammatory environment intestinal macrophages may be unable to aid in the development of Tregs resulting in reduced Treg frequency. Intestinal Dendritic Cells In general DC sample antigens from the environment and present them to T cells Upon activation, DC express high levels of MHC, co stimulatory molecules, and
30 cytokines necessary for the activation, proliferation, and polarization of T and B cells. In this way, they regulate and direct the adaptive immune response. Intestinal DCs reside in the mesenteric lymph nodes (MLN), peyers patches (PP), small intestine LP and colon LP 165, 166. Intestinal DC have specialized properties and function from conventional DC. For example, activated D C from the PP express higher levels of IL10 and are able to induce higher levels of IL4 and IL10 in nave CD4+ T cells than DC from the spleen 167. A subpopulation of intestinal DC express es CX3CR1 and resides within the LP wh ere they extend dendrites into the lumen and sample luminal content 168. While CX3CR1+ DC have been described as the most efficient in sampling luminal content they also polarize nave CD4 T cells towards a Th17 phenotype 169. For instance, in vitro CX3CR1+ CD70+ LP DCs induce CD4 T cells to produce IL 17 in the pr esence of ATP 170. In addition, in CX3CR1 / animals transfer of colitis is attenuated due to 171. The role of IL17 producing T cells in mucosal immunity will be expanded on below. Another intestinal DC subpopulation which express CD103+ are more efficient in the priming CD4 and CD8 T cell responses than CX3CR1+ DC, primarily due to their ability to migrate to the MLN 172. But unlike the Th17 phenotype induced by CXCR1+CD70+ DCs, CD103+ DC induce nave T cells to express FoxP3 173176. CD103+ DCs induce FoxP3 expression via the expression of retinoic acid (RA), a metabolite of vitamin A, transforming growth factor beta (TGF2,3dioxygenase (IDO) 175, 177, 178. Retinoic acid, as well as TGF is made by both CD103+ DCs and stromal cells within the MLN 175 where a substantial proportion of proliferating
31 T cells are express ing FoxP3 175, 1 76. In addition, CD103+ DC induce the expression of intestin cells Expression of these intestinal homing markers recruits and retains T cells within the mucosal environment. Regulatory T cells and Mucosal Tolerance In the intestine, Tregs play a critical role in maintaining hom eostasis and achieving oral tolerance. A ntigen specific Treg clones are found in peyers patches (PP) in orally tolerized mice 179. Similarly, it has been demonstrated that CD25+CD4+ Tregs are generated in the mesenteric lymph nodes (MLN) in oral ly tolerized ovalbuminT cell receptor transgenic mice 180. Trafficking of T cells to the GALT plays an important role in mucosal homeostasis, oral tolerance, and prevention of autoimmunity. Expression of mucosal addressin cell adhesion molecule 1 (MAdCAM 1) on the endothelium allows for T cells expressing the mucosal homing in gut via MAdCAM these molecules are unable to be orally tolerized 181. It has been demonstrated that CD4+ T cells need to migrate to the gut to be exposed to IL10 i n order to become fully tolerogenic 181. Additionally, IL10 expressing myeloid LP cells are able to sustain FoxP3 expression in T cells 182, suggesting that exposure to the LP environment can stabilize a regulatory T cell phenotype. Other supporting evidence suggest that Tregs migrate to and undergo expansion within the LP 183. Another mucosal i cells to interact with the epithelium via E +CD25+ Tregs are more CD25+, again suggesting that the mucosal environment supports peripheral immune tolerance. 184.
32 Th17 Cells transcription fac tor T be a subset of T cells distinct from the Th1 subset [reviewed in 185]. Nave T cells in IL 6, and IL 186188. IL 6 can induce expression of IL21 which can synergize with the above cytokines to induce expression of the IL23 receptor (IL23R) 189, 190. IL 23 interaction with its receptor on CD4+ + IL 17A+ cells expands and fully matures the T cells into Th17 cells 191, 192. In both mice and humans under steady state conditions, there are a low number of Th17 cells with a majority of them accumulating within the intestine 185, 193, 194. Here Th17 cells function to maintain the epithelial barrier and to help defend from extracellular bacterial invasion. Th17 effector cytokines are criti cal for defense against infections and include IL17A, IL17F, and IL22 195. Receptors for IL17A, IL17F, and IL22 are expressed on the epithelium throughout the intestine, therefore Th17 cells provide communication between the mucosal immune system and the intestinal tis sue 185, 195. IL 17A and ILdefensin by the epithelium and recruits neutrophils to sites of inflammation 196198. IL 17A and IL17F also induces expression of CCL20 by the epithelium. CCL20 can bind to the receptor CCR6 which is highly expressed on Th17 cells, in order to retain or recruit Th17 cells in the gastrointestinal track 193. IL 22 also induces expression of antimicrobial peptides from epithelial cells 195, 199, while promoting epithelial survival, proliferation, and tissue repair within the intestine 200202.
33 Although Th17 cells play a signi ficant role in mucosal homoestais, several autoimmune models such as experimental autoimmune encephalomyelitis (EAE), collageninduced arthritis (CIA), and inflammatory bowel disease (IBD) which were incorrectly considered to be Th1mediated diseases are now considered Th17 mediated diseases 203205. It is now known that IL23, not IL 12, though they both share the p40 subunit, is required for these diseases and has given rise to a new Th17 mediated pathogenesis paradigm 206. Unlike Th1 cells, which do not upregulate the IL23R, Th17 cells express both the IL23R and the IL12R and can respond to IL23 or IL12 207. Using an IL 17F reporter mouse model, it was determined that Th17 cells could change their cytokine expression depending on the mileu of cytokines with which they were stimulated 207. The stimulation with various cytokines resulted in cells that had high expression of IL17A/F, low expression of ILexpressed both IL207. Several studies suggest that Th17 cells are able to progress producing cells in vivo. First, transfer of Th17 cells from an IL17F reporter mouse into immunodeficient hosts induced colitis and shifted the Th17 cells to express reduced levels of IL17A, lose expression of IL17F, and upregulate expression 207. Second in an antigen specific model for ocular inflammation, a substantial fraction of Th17 cells adopted a more Th1 phenotype through expression of 208. Finally, two groups reported that transfer of Th17 transgenic BDC2.5 T cells induced insulitis and diabetes after adopting a Th1 phenotype 209, 210. Both groups lls producing 209, 210.
34 Several mechanisms within the mucosa have evolved to control the effector function of Th17 cells including prevention of Th17 differentiation. High concentrations ting Th17 differentiation 175, 190 211. Similarly, IL 2 212. Specifically, IL 2 induces p STAT5, which competes with the STAT3 binding site on the IL 17A locus and inhibits Il17a transcription 213. Prevention of Th17 differentiation is one way of regulating Th17 responses, but once a strong Th17 response oc curs additional regulatory mechanisms are called into play. For instance, Foxp3+ Tregs have been shown to suppress Th17 cells ex vivo 214, 215. In addition, Th17 cells have demonstrated great plasticity in their phenotype and effector function. For instance, Th17 cells typically reside within the ileum, where during strong Th17 responses they are recruit ed to the duodenum on a CCL20 chemokine gradient 193. Here effector Th17 cells are eliminated into the lumen due to tissue destruction and diarrhea. The remaining Th17 cells are reprogrammed to a more regulatory phenotype and express high levels of IL10 and have suppressive capacity through TGF4 193. The mechanism through which these cells were reprogrammed is still unclear. Similar to Th17 cells, Tregs also exhibit plasticity where a dualistic function of 186188. 216, thus in an environment Treg cells are favored depending on whether IL6 is present or absent. Tregs can be induced to express IL17 and downregulate Foxp3 by stimulation with IL6, suggesting that Tregs can become Th17like 217. Thus far the reciprocal conversion, from Th17 to
35 Treg, has not been described, suggesting that the conversion from Treg into Th17like may be irreversible 218. This would have important implications for autoimmunity and the autoimmune process, because if the environment favors conversion of Tregs into Th17like cells it may result in a permanent loss of promoting environment, a more inflammatory Th17 phenotype would also prevail. Mucosal Immunity and T1D Diet and T1D Dietary factors seem to have an influence on development of T1D. For example, there is increasing evidence of an association between celiac disease (CD) and T1D. Celiac disease is an intestinal autoimmune disease triggered by exposure to gluten which is found in cereal proteins. After exposure, CD patients exhibit inflammation that leads to destruction of the epithelium which results in loss of villous structure and impairs absorption of nutrients 219. Both T1D and CD share high susceptibility with the HLA DQ2/DQ8 genotype and they share almost half of the susceptibility alleles associate with T1D 220. It has been shown in rodent models for T1D that a cereal based diet promotes development of the disease 221, 222. In NOD mice, it has been demonstrated that a lifelong gluten free diet decreased incidence 223 and that a delayed exposure to wheat and barley proteins also decreases incidence 224. These studies suggest a relationship between exposure to dietary gluten and the development of T1D. Evidence of Mucosal Inflammation in T1D Increasing evidence suggests that the mucosal immune system is involved wit h development of T1D. It has been observed that pediatric patients with T1D have an increased expression of major histocompatability complex (MHC) class II as well as
36 ICAM 1 on the epithelium suggesting activation 225, 226. Additionally, a higher frequency 4 positive cells were found to be located in the lamina propria in patients compared to diabetes free participants 226. These findings suggest that the gastrointestinal mucosal immun e system is activated in T1D patients. In the NOD mouse, it has been observed that disease causing T cells are located within the MLN as early as 3 weeks of age 227, where MLN lymphocytes display a higher diabetogenicity compared to the PLN lymphocytes upon adoptive transfer Additionally, islet gut associated lymph tissue ( GALT ) specific integrin. T cells during t he prediabetic phase typically express this integrin whereby 228, 229. Interestingly, around time of weaning endothelium within the NOD mouse pancreas begins to express MAdCAM 228. This suggests that the change in diet may be contributing to the T cells homing to the pancreas. Some human studies support these findings, where GAD reactive T cells from T1D patients express also express 230 and lymphocytes from pancreas of T1D individuals were able to adhere to both the mucosal and pancreatic endothelium 231. Together these data suggests that autoimmune activation can occur within the GALT and contribute to migration of autoreactivity to the target organ 232. G astrointestinal Alterations in T1D Gastrointestinal (GI) alterations have been observed in both rodent models of T1D and in T1D patients. Biobreeding diabetes prone rats exhibit several GI alterations including increased intestinal permeabi lity, greater crypt depth, abnormal epithelial cell
37 proliferation, and inflammatory lymphocyte infiltration prior to development of insulitis and diabetes 233236. Human studies support that there are GI alterations in T1D. A study evaluating patients at varying stages of disease demonstrated that all patients exhibited an increase in permeability and that a compromise in barrier function occurred prior to clin ical onset of T1D 237. Another study examined nonceliac T1D patients where these patients exhibited increased permeability and structural changes in microvilli and tight junctions compared to diabetes free controls 238. Finally, it has been demonstrated that pediatric T1D patients with the genotype HLA DQ2 also e xhibi t increased gastrointestinal permeability 239. Together, these studies suggest that a compromised intestinal function or even an intestinal defect may play a role in the disease. S omewhat recently it was demonstrated that zonulin, a host protein involved with the disassembly of tight junctions may be contributing to the alterations in intestinal permeability observed in T1D240. Zonulin can cause disruption of the tight j unctions through interaction with proteinaseactivated receptor 2 ( PAR2 ) which can lead to activation of the EGF receptor (EGFR) or through direct interaction with EGFR. The activation of EGF receptor leads to increased permeability 240. Zonulin has been found to be upregulated in a number of autoimmune diseases including CD and T1D 241244. As mentioned previously, studies have shown an increase in intestinal permeability occurs prior to clinical onset of disease. Thus, using the BBDP rat model, it was demonstrated that zonulin dependent increases in intestinal permeability occurred 23 weeks prior to onset 245. Additionally, the study demonstrated that oral administration of the zonulin inhbitor, AT1001, decreased intestinal permeability,
38 blocked autoantibody formation, and decreased incidence of disease 245. These studies showed that in the BBDP rat model for T1D zonulin dependent loss of barrier function contributed to the initiation of the disease. In humans, preliminary studies suggest that zonulin is upregulated prior to disease onset 246. Interestingly, this same study reported that about 25% of unaffected family members of patients with T1D exhibited increased zonulin levels and an increase in intestinal permeability without progressing into disease, suggesting that loss of barrier function is not sufficient for disease progression 246. Hypothesis and Summary As describe above, there is increasing evidence supporting a role for the mucosal immune system in the development of T1D. We particularly found evidence of increased intestinal perm eability prior to disease onset in both humans and in rodents intriguing. When paired with the evidence of mucosal inflammation in humans and in rodents, the question then became: which occurs first? This question drove us to our hypothesis: that a break down in intestinal barrier function results in an inflammatory environment that promotes nontolerizing conditions.
39 CHAPTER 2 MATERIALS AND METHODS M urine Models NOD/LtJ mice were bred and housed under speci free conditions Mice were maintained in an American Association of Laboratory Animal Care accredited facility, and all procedures were approved by the University of Florida Institutional Animal Care and Use Committee NOD/LtJ and C57Bl/6 mice were sacrificed at 4, 8, 12, and 16 weeks of age. At time of sacrifice, intestinal segments, MLN, and PLN were harvested. Gastrointestinal Permeability Immediately following euthanasia, the whole small intestine was removed and placed into 150mM NaCl. Sections for the proximal jejunum (located ~ 5 cm from the stomach, proximal portion of the proximal jejunum ), the distal ileum (located just above the caecum distal portion of the distal ileum ), and the distal colon (distal portion of the distal colon) were isolated. Remnants of connective tissue were removed with dissection tools and the intestinal segment was opened along the mesenteric border. Flat sheets of tissue were mounted in modified Ussing chambers having an exposed tissue area of 0.3 cm2. Serosal to mucosal flux of [14C] mannitol specific activity 50 60 mCi/mmol, and [14C] dextran, specific activity 0.52 mCi/g ( American Radiolabeled Chemicals, Inc, Saint Louis, MO) were measured across tissues bathed on both sides by 4 ml of buffered saline (pH 7.4) at 37% O2 5%CO2. The standard saline contained the following solutes (mmol/L): 114.8 NaCl, 1.4 KCl, 1.6 K2HPO4, 0.4 KH2PO4, 25.0 NaHCO3, 10.0 Glucose, 1.0 MgSO4 7H2O, 1.0 CaCl2 2H2O. The standard buffer also contained 10 uM indomethacin to inhibit prostanoid production.
40 A concentration of 1mM of [14C] mannitol and 0.1uM of [14C] dextran in standard buffer was used for experiments. Radiolabeled mannitol or dextran was added to the serosal side and movement measured at 15 minute intervals for 45 minutes by sampling 1 mL of the buffer on the mucosal side. The activity of the samples were then measured on a scintillation counter (Beckman LS6500, BeckmanCoulter Inc ) Experiments were performed under short circuit conditions using an automatic voltage clamp ( VCCMC6; Physiologic Instruments, San Diego, CA ). The electrical parameters of the tissue were recorded at 15 minute intervals throughout the experiment. Tissue conductance (Gt; mS/cm2) was calculated as the ratio of the open circuit potential (V; mV) to the short circuit current (Isc; A/cm2). Fluxes (Jsm; nmol/cm2/hr) of tissues were calculated using the FLUXers Fantasy program developed by Robert Freel, PhD, Department of Pathology, College of Medicine, University of Florida. Flow Cytometry Spleen (S PLN), mesenteric lymph node (MLN) and pancreatic ly mph node ( PLN) were ground between glass slides to achieve single cell solutions in PBS. Spleen solutions were placed into red blood cell lysis buffer (8. 3g NH4Cl, 1.0gKHCO3, 1.8mL of 5% EDTA, in 1L dH2O) for 1 0 minutes at room temperature, pellet ed (1200rpm, 10 min) and resuspended in FACS buffer (1% FBS/PBS/2mM EDTA). Cells were then plated in 96 well plates with 5 ug/ml of plate bound CD3 (eBio 145 2C11) and soluble CD28 (eBio 37.51) for 3 days Afterwh ich cells were incubated for 4 hours with 10ng/ml of PMA, 1ug/ml of Ionomycin and 10ug/ml of B refeldin A (Sigma) Polyclonally expanded SPLN, MLN, and PLN cells were stained for extrac ellular markers in FACS buffer for 30 minutes on ice, pelleted (1200 r pm, 10 min) and washed 3x with FACS buffer. Cells were then fixed and permeablized with Cytofix/Cytoperm
41 ( Becton Dickinson, Franklin Lakes, NJ ; 512090KZ) solution for 30 minutes on ice. The extracellular stained cells were washed 3x with Perm/Wash ( Becto n Dickinson; 512091KZ) and stained with intracellular cytokine abs for 1 hour in BD Perm/Wash solution on ice. Samples were pelleted (1200 rpm, 10 min) washed 3x with Cytofix/Cytoperm and resuspended in FACS buffer containing 4% PFA. Data were acquired u sing a BD Accuri (Becton Dickinson) and analyzed using BD Accuri C6 software (Becton Dickinson). Antibodies were purchased from BD Bioscience and eBioscience and used at 1:200 dilution for analysis of CD4+ T cells: FITC anti CD4 (eBio RM4 5), APC anti(eBio XMG1.2), PerCPCy5.5 anti IL 17A (BD Bio TC11 18H10),andPE anti IL 4 (eBio 11B11) ELISA A capture ELISA was used to measure levels of TNFduodenum. Sections of duodenum (~1.2 cm, normalized by weight 0.085g) were obtained and homogenized using a MiniBeadbeater TM ( Biospec Products ) and 1.0mm Zirconia/Silica beads (Biospec Products 11079110z). Samples were then centrifuged using a BD OptEIA ELISA kit (BD OptEIA TNF well plates were coated with a 1:250 dilution of capture anti coating buffer (8.40g NaHCO3, 3.56g Na2CO3, pH 9.5) and incubated overnight at 4C. Plates were blocked in 10%FBS/PBS for 1 hour. Plates were washed 3x with wash buffer (PBS 0.05% Tween20). 50ul of supernatant was added per well and incubated at room temperature for 2 hours. Plates were washed 5x with wash buffer and incubated with 1:250 dilution of biotinylated anti at room temperature for 1 hour. Plates were washed 5x with wash buffer and streptavidinhorse radish peroxidase (HRP) was added at a 1:250
42 dilution and incubated for 30 minutes. After washing 7x with wash buffer, plates were developed for 30 minutes in the dark at room tem perature using 100ul of TMB substrate solution. Data was acquire on a spectrophotmeter (Biotek Epoch) at (450nM) and (570nM) where (450nm 570nm). Cytokine concentrations in culture supernatants were determined using a standard curve. Statistics The following data are presented as mean SEM. Comparisons between NOD and B6 mice were made by unpa ired Students t test. Comparisons between NOD MLN and PLN ages were made by unpaired Students t test, since ANOVA analysis could not be conducted due to low sample number A Spearmans correlation and linear regression was made between Jsm dextran and GT. The results were accepted as significant at P < 0.05. Statistical analysis was carried out using GraphPad Prism 6 and figures were drawn in GraphPad Prism 6.
43 CHAPTER 3 RESULTS In order to address our hypothesis, we temporally evaluated intestinal barrier function and inflammation. The effect of changes in barrier function and inflammation on MLN and PLN T cell phenotypes was also evaluated. Time points for evaluation were chosen based off of the well characterized disease checkpoints of disease progression within the NOD mouse 48. Thus, we evaluated mice at 4, 8, 12, and 16 weeks of age. As a control for our NOD mice, we used the genetically distinct C57Bl/6 mic e which do n ot exhibit autoimmunity (Figure 31). To evaluate intestinal barrier function, we measured transcellular movement of charged ions through and paracellular permeability of the small and large intestine by conducting flux experiments utilizing Ussing chambers. Specifically, the movement of [14C] mannitol across specific sections of intestine measured paracellular permeability, while the electrical parameters were used to determine the movement of charged ions across the tissues. Data generated here would allow us to determine if, when and, where there are alterations in gastrointestinal permeability during T1D disease progression. To evaluate general intestinal inflammation, we evaluated levels of inflammatory cytokines in homogenized intest ine by ELISA. T1D is primarily a T cell mediated disease due to loss of central and peripheral tolerance. In addition, there is strong evidence of autoreactive T cells residing in the MLN at early stages of disease 227. Thus we also evaluated T cell populations within the MLN and PLN over the course of the disease.
44 Our final goal was to determine if a rise in the gastrointestinal inflammatory environment was a cause or consequence of loss of barrier function and its effect on peripheral tolerance as measured by T cell phenotypes in the gastrointestinal track and target organ. Intestinal Permeability Previous studies have demonstrated alterations in GI functi on associated with T1D in humans and mice 233239, whereby there was increased permeability as measured by lactulose:mannitol leakage. Though these experiments do answer the question of whether there are alterations in permeability, they do not temporally evaluate permeability or evaluate specific sections of intestine for differences in permeability. Thus whether this is a consequence or cause of immunological phenomenon observed in T1D is still unclear. Therefore, in order to temporally evaluate specif ic intestinal sections for differences in permeability, we utilized in vitro analysis of gastrointestinal charged ion movement and paracellular permeability using Ussing chambers. S ections of proximal jejunum and distal ileum, both located within the small intestine, as well as distal colon, located within the large intestine were harvested. Tissue sections were mounted in Ussing chambers and measurements for flux of [14C]mannitol (Jsm mannitol) across the short circuited tissue sections were obtained. Electrical parameters were also obtained. Specifically, short circuit current (Isc) and open circuit potential (V), were measured at 15 minute intervals for 45 minutes. Conductance (GT) was determined as the ratio of V to Isc and relates to the permeabili ty of the tissue. [14C] mannitol can be used as a marker for paracellular permeability
45 while electrical parameters can be used as an indicator of movement of charged ions if no differences in paracellular permeability are present. Movement of Charged I on D iffers between NOD and B6 M ice Initially, in conjunction with a collaboration with Dr. Marguerite Hatch, Department of Pathology, College of Medicine at the University of Florida, the short circuit current (Isc) and open circuit potential (V), were measur ed and the conductance (Gt) calculated in the distal ileum (DI), and proximal jejunum (PJ) (Figure 32 ). It was determined that that GT of the proximal jejunum and the distal ileum from B6 mice was higher than that observed in tissues from NOD mice through out the course of disease (Figure 32 C, F ). The higher GT was most likely due to the higher Isc also exhibite d by tissues from B6 mice (Fig ure 32 B, E). For paracellular permeability, i t was determined that there were no differences in the Jsm mannitol o f tissues from NOD and B6 mice until 16 weeks of age (Figure 32 A, D). Thus, without differences in paracellular permeability, the differences in Isc and Gt, indicate smaller movement s of charged ions within the small intestine of NOD mice compared to those of B6 mice. Preliminary Flux Trials After a period of shadowing Dr. Hatch, I needed to improve my skills with the techniques used for flux measurements. Dissection and mounting of the intestinal tissue are technically demanding aspect of the experiment where incorrectly handled intestine can significantly alter permeability of the tissues. Thus, a series of flux trials was performed in order to evaluate the reproducibility of the assays following my training (Fig ure 33) Initially, we compared GT a nd Jsm mannitol from B6 mice with measurements from previous experiments performed by Dr. Hatch (Table 1) Although my initial experiments had high levels of variation (Trial 1; Figure 33 ), by the third trial of
46 experiments, the variation was significantly lower and measurements were within similar ranges of those obtained by Dr. Hatch ( Table 1). Specifically, within the distal colon, the GT lowered each trial and by the third trial measurements had come into acceptable range (~1520mS//cm2) indicating that handling of the t issue had improved with each tri a l whereby the integrity was not compromised (Figure 33 A) Similar results were seen for the GT and Jsm mannitol of the distal ileum and proximal jejunum (Fig. ure 3 3 B, C, E, F) Specifically, the meas urements of mannitol flux across the distal ileum and proximal jejunum was initially very high suggesting that handling of the tissue was not optimal (Figure 33 E, F) which significantly improved over the subsequent trials. 70kDa Dextran as a Paracellular Permeability M arker After evaluating the movement of mannitol as a marker for paracellular permeability and seeing no differences between NOD and B6 mice we decided to evaluate paracellular permeability using a larger molecule. Mannitol is a small mol ecule (~4 in diameter) and it is possible that it is not large enough to distinguish small changes in paracellular permeability. Indeed a study investigating the role of tight junctions in size exclusion of macromolecules observed greater fold differences in paracellular permeability when using larger molecules 247. Thus, we decided to use [14C] 70kDa dextran which is significantly larger (~36 diameter) than mannitol and therefore should be more sensitive to small changes in permeability. I initially evaluated [14C] 70kDa dextran flux (Jsm dextran) as described for [14C] mannitol (Fig ure 34) Experiments were conducted on the proximal jejunum and distal ileum as well as the distal colon from B6 mice. I observed similar GT measur ements as previously shown (Figure 33), but I now observed much lower movement of 70kDa
47 dextran when compared to [14C] mannitol (Figure 34). Therefore, I wanted to determine whether 70kDa dextran could be used as a paracellular permeability marker. To artificially increase paracellular permeability, we conducted experiments in the absence of Ca2+ (Fig ure 34) Using a Ca2+ free buffer results in loss of tight junction integrity t herefore causing a decrease in electrical resistance or an increase in conductance (GT) 248. Thus, if we decrease tight junction integrity and see an increase in GT, then we would expect to see greater par acellular movement of dextran. Indeed when comparing Jsm dextran to GT for experiments done in standard buffer with the experiments done in Ca2+ free buffer, we determined that dextran movement (Jsm dextran) increases as the GT increases (Figure 34). This positive correlation suggests that dextran could be used as a paracellular marker in future experiments D ue to its larger size it may provide more sensitive marker of paracellular permeability. Duodenal Tissues of NOD Mice when C ompared to B6 Evidence of intestinal inflammation has been observed in rodent models for T1D and in human patients 225232 increased permeability by modification of tight junctions and even cell death, while regulatory cytokines, such as IL10, have been shown to support barrier function [reviewed in 249] Thus, in order evaluate mucosal inflammation at key disease checkpoints 48 B6 mice by ELISA (Figure 35) At both early and late stages of disease, we observed duodenum of NOD mice compared to B6 mice (Figure 35). First, this suggests that there is inflammation in the intestine of NOD mice even at early stages in disease. Second, this suggests that there could be effects on tight
48 junctions in NOD mice, which were not detected in the evaluation of paracellular permeability as measured by movement of [14C]mannitol (Figure 32 ). T cell Population Differences between NOD and B6 M ice As outlined in the background, the mucosal environment can regulate and polarize nave T cell responses. Thus, we evaluated T cell phenotypes within the draining lymph nodes of the gastrointestinal track (MLN). In addition, we wanted to determine the evolution of T cell inflammation/phenotype in the MLN and the target organ over the course of disease. Thus we also evaluated T cell phenotypes within the draining lymph nodes of the pancreas (PLN). In order to evaluate T cell phenotypes, we first started by evaluating populations of CD4+ T cells. We initially characterized the phenoty pe of CD4+ T cells from the MLN and PLN via flow cytometry. Specifically the percen+ (Th1), IL 17A+ (Th17 IL17 only + IL 17A+ (Th17 IL17 ) were determined (Figure 36 C) Th1 T cells have been shown to be key mediators in the pathogenesis in T1D 9296. On the other hand depending on the phenotype of Th17 cells they play an important role in mucosal homeostasis or play a role in induction and maintenance of autoimmunity 250. Overall a higher frequency of CD4+ T cells which were polarized to express cytokines were observed in both the MLN and PLN of NOD mic e when compared to B6 mic e (Figure 37 ). Specifically, in the MLN, a higher frequency was observed at 4, 8, and 12 weeks of age (Figure 37 A ), while in the PLN, increased frequencies were observed at all checkpoints of disease in NOD mice (Figure 37 B ). Interestingly, the freq uency of CD4+ T cells within the MLN of NOD mice which were polarized to express cytokines (at least those we evaluated) appears to decline over the course of the disease (Figure 37 A ). Conversely, the frequency of CD4+ T cells within the PLN
49 appears to increase over the course of the disease (Figure 37 B ). These data suggest that there is increased inflammation within the MLN at early checkpoints prior to the increased inflammation observed at later checkpoints in the PLN. Th17 and Th1 D ifferences between NOD and B6 M ice As has previously been published, Th1 cells are elevated in the PLN which increase in frequency over the course of the disease in NOD mice and are have been cell destruction 251, 252. In deed NOD mice + T cells in the MLN at both 4 and 8 weeks of age when compared to B6 (Figure 38 C ). Although, after 8 weeks of age this population sharply declined in the MLN of NOD mice, but was still higher than the frequencies observed in B6 mice at 12 weeks of age and was normalized by 16 weeks of age (Figure 38 C ) expressing CD4+ T cells at every checkpoint in the disease when compared to B6 mice (Fig ure 38 D) As expected, this population continued to rise within the PLN of NOD mice over the course of the disease (Figure 38 D ). It is plausible that elevated Th1 cells within the MLN could be contributing to intestinal inflammation within the NOD mice at early checkpoints or could be a result of intestinal inflammation causing improper Th1 polarization. As mentioned previously, Th17 cells are predominantly found within the intestine and play an integral part in regulation of the mucosal immune system. Th17 cells that express only IL17 and are more regulatory in nature 250, while Th17 cells that co17 have been implicated in a number of different autoimmune diseases including T1D 206, 253. In the MLN, NOD mice exhibited a higher frequency of IL17+ only CD4+ T cells at each disease checkpoint when compared to B6 mice (Figure
50 3 7 A ). Again within the MLN this population decreased over the course of the disease progression (Figure 38 A ). On the other hand, similar frequencies of IL17+ only CD4+ T cells were observed in the PLN of B6 and NOD mice at 4 and 8 weeks of age (Fig ure 38 B) Interestingly there was a rise in frequency of IL17 only expressing cells in the PLN of NOD mice at 12 weeks of age compared to B6 mice which remained elevated t o at least 16 weeks of age (Figure 38 B ). As IL17 has been shown to have synergistic effects with IL increasing their ability to induce cytokine induced death 254, it is possible that the elevated levels of IL17 only expressing cells at later cell destruction. The frequencies of IL17+ + expressing CD4 T cells in the MLN of NOD mice were higher at earlier checkpoints at disease when compared to B6 mice (Figure 38 E). In addition, their frequencies declined over the course of disease in the NOD mouse (Fi g ure 38 E ). In the PLN, similar frequencies of this population were observed at 4 weeks of age between NOD and B6 mice (Figure 38 F ). By 8 weeks of age NOD mice exhibited a higher frequency of IL17+ + when compared to B6 mice which continued to ris e over the course of the dis ease (Figure 38 F ). Again, in NOD mice, it seems there is elevated inflammation in the MLN at early checkpoints, and within the PLN at later checkpoints as measured by frequencies of IL17+ IFN+ CD4+ T cells. NOD MLN and PLN T c ell Populations over the Course of the D isease We next evaluated the temporal evolution of these T cell populations within the MLN and PLN of NOD mice. Interestingly for each population of T cells, IL17+ o nly, + only, and IL17+ +, a decrease in frequency in the MLN over time and an increase in frequency in the PLN over time was observed (Figure 39 ). There are a few explanations that are possible and can be further pursued in future experiments. First, it
51 is possible that these cells are migrating from the MLN to the PLN as the disease progresses. Second, due to the known plasticity of these cells it is possible that T cells residing at either location are changing phenotypes over the course of the disease. Decreased Treg Frequency in the MLN and PLN of NOD M ice Previous studies have shown a decrease in the frequencies of Tregs in NOD mice 255 which res ults in alterations in peripheral tolerance. In addition, the induction of Tregs can be regulated by the mucosal immune system 179, 180. Thus, we also evaluated the expression of C D 4+CD25+FoxP3+ Tregs within the MLN and PLN of NOD and B6 mice over the course of disease (Figure 36 D) As previously published, NOD mice exhibited lower frequencies of Tregs at each stage of the disease in the MLN and PL N when compared to B6 mice (Figure 310 ). Interestingly, the frequency of Tregs within the MLN decreased as B6 mice aged, though relatively stable frequencies were observed in the PLN (Figure 310 ). While there were lower frequencies of Tregs within the MLN of NOD mice compared to those observed in the PLN, but there was no change in either lymph node over the course of disease progression (Figure 310). The observed lower frequencies of Tregs, could be insuffici ent to suppress inflammation, and thus explain why NOD mice exhibit higher frequencies of T cells expressing inflammatory cytokines when compared to B6 mice.25
52 Table 31 Gastrointestinal Barrier Function Analysis. a G T x (ms/cm 2 ) J sm mannitol (nmol/cm 2 /hr) D istal Ileum 31.39 2.34 n=7 31.6 5.4 n =8 Proximal Jejunum 20.94 1.84 n=15 24.13 2.71 n =14 Distal Colon 19.44 1.58 n =6 31.78 3.95 n =5 adata generated by Dr. Marguerite Hatch Department of Pathology, University of Florida GT = the ratio of the open circuit potential (V; mV) to the short circuit current (Isc; A/cm2) Jsm mannitol= serosal to mucosal movement of mannitol
53 Figure 31 Temporal Evaluation of Intestinal Barrier Function and Inflammation Intestinal sections along with mesenteric and pancreatic lymph nodes were harvested at indicated disease checkpoints. A ) Using chambers were used to to conduct paracellular permeability and transcellu la r movement of ions to evaluate barrier function ex vivo. B ) Gastrointestinal inflammation was assessed via soluble mediator expression and T cell phenotypes nodes at indicated disease checkpoint s. Soluble mediators were evaluated in homogenized tissues via ELISA. T cell phenotypes were evaluated via flow cytometry from mesenteric and pancreatic lymphocytes.
54 Figure 32. Decreased Gastrointestinal Movement of Charged Ions in NOD mice. I ntestinal sections of proximal jejunum A,B,C) and distal ileum D,E,F ) were harvested and placed into Ussing chamber s. [14C] M annitol movement and electrical parameters were measured over a 45 minute time period. A,D) Measurement of [14C] mannitol movement from the serosal to the mucosal (Jsm) side of the tissue. B,E) Isc or short circuit current is indicative of ion movement. C,F) GT measurements ( GT is the ratio of voltage to Isc (short circuit current)). n=415 tissues per strain per age. *p value = <0. 05, Students T test
55 Trial 1 Trial 2 Trial 3 0 10 20 30 40*GT(mS//cm2) Trial 1 Trial 2 Trial 3 0 10 20 30 40Jsm(nmoles/cm2/hr) Trial 1 Trial 2 Trial 3 0 50 100 150 200* *GT(mS//cm2) Trial 1 Trial 2 Trial 3 0 50 100 150* *Jsm(nmoles/cm2/hr) Trial 1 Trial 2 Trial 3 0 20 40 60 80 100*GT(mS//cm2) Trial 1 Trial 2 Trial 3 0 50 100 150*Jsm(nmoles/cm2/hr)A. B. C. D. E. F. Figure 33 Optimization of Gastrointestinal Permeability Assay s. Intestinal segments of the A,D) d istal colon, B,E) distal ileum and C,F) proximal jejunum were harvested from C57Bl/ 6 mice and placed in Ussing chambers [14C] Mannitol movement and electrical parameters were measured over a 45 minute time period. A,B,C) C onductance (GT = ratio of voltage to Isc (short circuit current) ) w as measured. D,E,F) Paracellular permeability was measured by tracki ng serosal to mucosal movement of [14C] mannitol (Jsm) n=56 tissues per trial. *p= <0.05 vs. Trail 1 Students Ttest
56 0 50 100 150 200 0 20 40 60 R2=0.52GT(mS//cm2)Jsm(pmoles/cm2/hr) Figure 34 Evaluation of 70kDa Dextran as a Paracellular Permeability Marker Distal colon, p roxim al jejunum and distal ileum segments were harvested from C57 B l/ 6 mice and mounted in Ussing chambers. [14C] Dextran movement and electrical parameters were measured over a 45 minute time period and analyzed. M ovement of [14C] dextran from the serosal to the mucosal side (Jsm) of the tissue was evaluated. GT (ratio of voltage to Isc (short circuit current) ) was calculated. Assays were conducted in both standard and Ca2+ free buffer Linear regression (R2=0.52) and Spearmans correlation (p value <0.001) w as performed between Jsm and GT in all tissues
5 7 Figure 35 NOD mice exhibit Elevated Duodenal TNF Levels Duodenum samples ( ~ 1.2 cm length, normalized by weight 0.085g) were harvested at indicated disease checkpoints and hom o genized via bead beating. TNF levels were measured by ELISA. *p value = 0.0011, Students Ttest
58 Figure 36. Gating schemes for Flow Cytometric Analysi s. MLN and PLN lymphocytes were harvested. T cells were expanded using plate bound anti CD3 and soluble anti CD28 for 3 days followed by incubation with PMA/Ionomycin and Brefeldin A for 4 hours A B) T cells were probed for B) CD4 and C) intracellular cytokines marker FoxP3. Panels C and D are gated on the red highlighted regions in panels A and B.
59 B6 NOD B6 NOD B6 NOD B6 NOD 0 25 50 75 100 125IL17+ IFNIL17-IFN+ IL17+IFN+ 4wks 8 wks 12 wks 16 wks MLN%CD4+ T cells B6 NOD B6 NOD B6 NOD B6 NOD 0 25 50 75 100 125IL17+ IFNIL17-IFN+ IL17+IFN+ 4wks 8 wks 12 wks 16 wks PLN%CD4+ T cellsA. B. Figure 37 Frequencies of Polarized T cells in the MLN and PLN A) MLN and B) P LN lymphocytes were harvested at indicated disease checkpoints. T cells were expanded using platebound anti CD3 and soluable anti CD28 for 3 days followed by incubat ion with PMA/Ionomycin and Brefeldin A for 4 hours T cells were probed for CD4 and intrac e llular cytokines n=2 mice per age per strain.
60 4 wks 8 wks 12 wks 16 wks 0 10 20 30 40 50 NOD C57Bl/6 MLN% IL17+IFN 4 wks 8 wks 12 wks 16 wks 0 5 10 15 20 NOD C57Bl/6 PLN% IL17+IFN 4 wks 8 wks 12 wks 16 wks 0 10 20 30 40 50 NOD C57Bl/6 MLN% of IL17-IFN + 4 wks 8 wks 12 wks 16 wks 0 10 20 30 40 50 NOD C57Bl/6 * PLN% IL17-IFN + 4 wks 8 wks 12 wks 16 wks 0 10 20 30 40 50 NOD C57Bl/6 * MLN% IL17+IFN + 4 wks 8 wks 12 wks 16 wks 0 20 40 60 NOD C57Bl/6 PLN% IL17+IFN +A. B. C. D. E. F. Figure 38 Frequencies of IL17 expressing T cell populations A,C,E) MLN and B,D,F) PLN lymphocytes were harvested at indicated disease checkpoints T cells were expanded using platebound anti CD3 and soluble anti CD28 for 3 days followed by incubation with PMA/Ionomycin and Brefeldin A for 4 hours. T n=2 mice per strain. *p= <.05, Students T test.
61 4 wks 8 wks 12 wks 16 wks 0 20 40 60 MLN PLN % IL17-IFN + 4 wks 8 wks 12 wks 16 wks 0 20 40 60 MLN PLN % IL17+IFN 4 wks 8 wks 12 wks 16 wks 0 20 40 60 MLN PLN % IL17+IFN +A. B. C. ^ ^ ^ ^ ^ ^ ^ Figure 39 Distribution of T cell populations within the MLN and PLN of NOD mice over the course of disease. MLN (solid line) and PLN (dotted line ) lymphocytes were harvested at indicated disease checkpoints from NOD mice T cells wer e expanded using platebound anti CD3 and soluble anti CD28 for 3 days followed by incubation with PMA/Ionomycin and Brefeldin A for 4 hours. T cells were probed for CD4 and intracellular cytokines A) I L17 only expressing T cell frequencies B) Th1 IFN only expressing T cell frequencies (Th1) and C) IL17 and IFN expressing T cell frequencies n=2 mice per strain, *p= <0.05 vs. MLN 4 weeks ^p= <0.05 vs. PLN 4 wks. Students T test. A NOVA was unable to be completed due to low number of samples.
62 4 wks 8 wks 12 wks 16 wks 0 2 4 6 8 10 NOD C57Bl/6 *% CD4+CD25+FoxP3+ 4 wks 8 wks 12 wks 16 wks 0 2 4 6 8 10 NOD C57Bl/6 *% CD4+CD25+FoxP3+ MLNA. B. PLN Figure 310 Decreased Frequencies of Tregs in the MLN and PLN of NOD mice. A) MLN and B) PLN lymphocytes were harvested at indicated disease checkpoints. T cells were expanded using platebound anti CD3 and soluable anti CD28 for 3 days followed by incubation with PMA/Ionomycin and Brefeldin A for 4 hours. T cells were probed for CD4, CD25 and the intracellular marker FoxP3. n=2 mice per strain *p= <.05 vs. NO D at same time point Students T test ANOVA was unable to be completed due to low number of samples.
63 CHAPTER 4 DISCUSSION Recent studies mentioned above have implicated a role of mucosal immunity in the development of T1D. Several studies conducted on rodent models for T1D as well as human studies have shown increased intestinal permeability and gastrointestinal inflammation associated with T1D. Thus, we hypothesized that a break in barrier function results in an inflammatory environment which promotes non tolerizing conditions. To address this hypothesis we temporally evaluated gastrointestinal barrier function and inflammation as well as the effects of these changes on MLN and PLN T cell phenotypes (Figure 31) Our study determined that NOD mice exhibit decreased movement of charged ions within the intestine when compared to B6 mice. We also determined that intestinal inflammation occurs early in the progression of disease while pancreatic inflammation occurs later in the progression Barrier fun ction. We initially measured barrier function through permeability experiments conducted in Ussing chambers using [14C] mannitol movement as a marker for paracellular permeability. NOD mice exhibited similar paracellular movement of [14C] mannitol compared to B6 mice for both the proximal jejunum and distal ileum (Figure 32 A, D). This finding was unexpected as prior studies using lactulose:mannitol tests observed increased intestinal permeability in BBDP rats [229, 230] as well as in humans . There are a few potential reasons as to why we observed no paracellular differences between NOD and B6 mice. Our initial thoughts were that mannitol was too small to determine paracellular differences and so we investigated using a larger marker, 70kDa de xtran (Figure 34). A second explanation could be that in NOD mice T1D progression does not involve a breakdown in paracellular
64 permeability. This explanation is unlikely as we see elevated intestinal inflammation in NOD mice (Fig ures 3 5, 3 6) and inf lammatory cytokines increase permeability of tight junctions 249. Despite an absence of differences in paracellular permeability, we did find that NOD mice ex hibited differences in the transcellular movement of charged ions NOD mice displayed decreased GT and Isc compared to B6 mice, but with measurable differences in mannitol paracellular permeability we concluded that NOD mice had decreased transcellular mov ement of charged ions (Figure 32 B, C, E, F). We wanted to determine whether decreased movement of charged ions is contributing to intestinal inflammation or whether intestinal inflammation is causing decreased movement of charged ions The decreased mov ement of charged ions was relatively constant throughout the disease (Figure 32 B, C, E, F). Intestinal inflammation on the other hand was present early in disease 5) and polarized T cell populations (Figure 36), but decreased over time suggesting that there is not a correlation between movement of charged ions and intestinal inflammation. Though we could not determine if there i s a correlation between the two, the decreased movement of charged ions proved to be an interesting finding. Firstly as mentioned above, the incidence of T1D has been rapidly increasing over the past century faster than genetics can account for suggesting that environmental factors are likely contributing to disease development. A recent paper determined that increased NaCl promotes development of pathogenic Th17 IL17A secreting cells that contribute to autoimmune disease 256. What's interesting about this finding is that processed foods have almost 100 times higher salt content than similar homemade meals 257, 258. Decreased movement of charged ions may contribute to an inability to deal with
65 increased NaCl content which could lead to development of pathogenic Th17 cells. Indeed we see increased frequencies of IL17 IFN positive T cells (Figure 37 E) and decreased frequencies of IL17 only T cells in the MLN of NOD mice compared to B6 mice (Fig ure 37 A). Though differences in the movement of charged ions start early and stay relatively similar throughout disease, inflammation of the intestine and pancreas exhibit changes over the course of the disease. Inflammation. As mentioned above, we evaluated general inflammation through ELISA analysis of homogeni zed duodenum for TNF levels. We found that NOD mice exhibited elevated levels of TNF at early and midstage checkpoints (4 and 12 weeks o f age) compared to B6 mice (Figure 35). Further checkpoints must be completed to ar to the T cell inflammation we see within the intestine. We saw elevated frequencies of polarized T cells in the MLN compared to B6 mice at early checkpoints which decreased in frequency over time (Fig ure 36 A). When specifically looking at IL17 only, IFNg only, and IL17 and IFNg expressing CD4 T cells we see a similar trend where initially there are higher frequencies and over time they reduce in the MLN of NOD mice (Figure 38). Together these suggest that there is intestinal inflammation occurring early in disease. Also to note, NOD mice exhibited lower frequencies of IL17 only Th17 cells compared to B6 mice in the MLN (Figure 37 A), while they exhibited higher frequencies of IFN only and IFN a nd IL17 expressing T cells (Figure 37 C, E). Once again, a more polarized Th1 T cell population could be indicative of intestinal inflammation or could be a result of intestinal inflammation. In contrast, we saw low frequencies at early checkpoints of polarized T cells and higher frequencies at later checkpoints in the PLN of NO D mice
66 compared to B6 mice (Figure 36). Additionally in the PLN, each specific T cell population increased over time for NOD mice meaning that pancreatic inflammation doesnt occur until later checkpoints in the disease (Figure 38). When compared to B6 PLN at all checkpoints (Figure 37 D, F), while IL17 only cells did not increase until after 8 weeks of age (Figure 37 B). We saw a steady rise in the frequency of IFNg only Th1 cell destruction T1D (Figure 38 B) 251, 252. The IL17 only and IL17 IFN populations sharply rose between 8 and 12 weeks of age and continued to increase out to 16 weeks of age (Figure 38 A, C). The sharp rise in these populations suggests tha t at this stage in the disease there are factors present that influence Th17 differentiation. To summarize we s aw a trend of early inflammation occur r ing with in the intestine, which decreased over the course of the disease, while in the pancreas inflammation increased over the course of the disease. There are a few potential explanations for this trend. First, it is possible that the T cells residing within the MLN are trafficking to the PLN over the course of the disease. This would explain why the frequencies decline in the MLN and rise in the PLN. W hen looking at specific populations, for example IL17 and IFNg expressing Th17 cells (Figure 38 C ), the correlation between the decline and rise is not distinct. This would suggest that this trend is mos t likely not due to trafficking, though a tracking experiment to see if the T cells migrate from the MLN to PLN would most likely be necessary to rule out this explanation. Second, it is possible that the T cells residing in the MLN or PLN are simply changing phenotypes over the course of the disease. Due to the plasticity of Th17 cells mentioned above and the importance of the
67 environment with which they are in, this explanation is most likely. The question then becomes how does the initial intestinal inflammation contribute to pancreatic inflammation? What's interesting about our findings is that the initial inflammation within the intestine suggests a nontolerizing env ironment. A nontolerizing env i r onment woul d result in decreased Tregs (Figure 39 ) as well as decreased tolerogenic DC and therefore polarized T cells (Figure 36 ). We know that luminal antigen can be processed and presented in the PLN suggesting that intestinal DC likely migrate to the PLN 259. Through decreased Tregs and non tolerizing DC it is p ossible that the intestinal env i r onment contributes to pancreatic inflammation. Thus, for future experiments we will be investigating DC populati ons and phenotypes in the MLN and PLN over the course of the disease. To summarize, we could not determine a correlation between a breakdown in barrier function and intestinal inflammation a lthough, we plan to do future flux experiments using a larger paracellular marker. We found that NOD mice exhibited decreas ed movement of charged ions at all stages of disease development, which potentially could be contributing to intestinal inflammation. We also found that there was increased intestinal inflammation occurring at early stages in disease while pancreatic inflammation occurred at later stages in disease.
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90 BIOGRAPHICAL SKETCH Michael Nelson grew up in Voorhees New Jersey He did his undergrad at Elizabethtown College in Pennsylvani a where he completed a B.S. in biology. He then went to University of Florida where he completed his Master of Science. He plans to continue working within the science field, possibly pursuing homeopathic medicine. He enjoys reading, video games, and travel.